Embodiments of the invention generally relate to electronic natural language processing, and more particularly, to identifying readability levels of a user question and natural language documents based readability indicators.
Traditional systems estimate a user's reading level by analyzing relatively large datasets, associated with the user, over several iterations. The more text samples that are analyzed, the more likely that the analysis yields reliable results. For example, some metrics that these systems use are: average word length and average words per sentence.